Individuals and organizations regularly seek to improve their systems for storing large amounts of data. For example, enterprise organizations may seek improved systems and techniques for compressing data or otherwise optimizing the efficiency of data storage. In one specific example, enterprise organizations may organize their data within a deduplication system. In general, deduplication refers to the process of removing redundant instances of the same data segment or portion when that data segment or portion is included multiple times within a larger collection of data. Deduplication processes may replace the redundant instances of the same data segment or portion with a reference to a single instance of the data segment. Deduplication may thereby reduce the amount of storage space used to store data, and may also obtain other efficiencies.
Of course, traditional deduplication systems rely on underlying physical, virtual, and/or software-based storage solutions to ultimately store the single instances of unique data segments. Because these underlying storage solutions are imperfect, they may sometimes fail and corresponding data segments may become corrupted. Moreover, because multiple disk images may reference the same unique data segment, a single data segment corruption may impact or compromise a wide range of customers and/or disk images. The instant disclosure, therefore, identifies and addresses a need for systems and methods for healing images in deduplication storage.